Practice and CultureDriving digital innovation and engineering within our national laboratory system and industry to execute organizational transformation.
The realization of digital engineering and model-based systems engineering requires workforce transformation to enable success. Engineering teams must migrate from paper-based methodologies to a data-first, data driven future. Systems engineering transitions to model-based systems engineering, migrating from document centric paradigms to model exchange. Drafting migrates from geometry focused computer aided design (CAD) to data focused building information management (BIM) and product lifecycle management (PLM). Workforce strategy, communications, and training are coordinated to execute organizational transformation.
Collaborations & Projects:
National Reactor Innovation Center (NRIC)
The National Reactor Innovation Center (NRIC) has led new advanced demonstration projects using a model-based systems engineering approach. SysML and LML models are developed and traced to traditional requirements artifacts to realize this vision. Activity models are integrated with Discrete Event and Monte Carlo simulation to check for correctness, integrate cost and schedule, and monitor expected performance. NRIC is working to develop integrations between MBSE, engineering, operations, and traditional CAD software to enable a full digital thread in design.
Versatile Test Reactor (VTR) Program
The Versatile Test Reactor (VTR) Program utilize digital engineering principles for design, construction, and operations to reduce risk and improve efficiencies. Digital engineering is an integrated, model-based approach which connects proven digital tools such as building information management (BIM) and systems engineering software tools into a cohesive capability. INL manages the authoritative source of truth for the VTR program with contractors and university partners interfacing with this data source. The VTR Program utilizes the IBM Jazz systems engineering solution, AVEVA BIM, and configuration management tools to realize this vision for reactor design. Additional functionality will be deployed and integrated during the construction and operations phases.
National Reactor Innovation Center (NRIC) Program
The National Reactor Innovation Center (NRIC) leads new advanced demonstration projects using a model-based systems engineering approach. SysML and LML models are developed and traced to traditional requirements artifacts to realize this vision. Activity models are integrated with Discrete Event and Monte Carlo simulation to check for correctness, integrate cost and schedule, and monitor expected performance. NRIC is working to develop integrations between MBSE, engineering, operations, and traditional CAD software to enable a full digital thread in design.
Applied Visualization Laboratory (AVL)
The Applied Visualization Laboratory contains several 3D immersive environments for scientists and engineers to walk into their data, examine it, and provide deep analysis in pursuit of their research. As mixed, virtual, and augmented reality technology evolves, the opportunities for portable, in-depth analysis of complex data sets increases. Augmented reality solutions are envisioned to allow researchers to have CAVE-like experiences anywhere. Web-based 3-D geographic information systems, mobile applications (for both phone and tablet) and serious games (games built for training or educational purposes) allow users to conduct research at their desks or in the field, enabling discovery outside the lab. Virtual reality exploration systems offer the ability to create visualizations of large data sets that can be projected and run in real-time simulations. Using six-degrees-of-freedom input devices – which allow a body to move forward and backward, up and down, left to right – and stereoscopic output, they offer the benefits of more realistic interaction.
The Center for Advanced Energy Studies (CAES) opened its first Cave Automatic Virtual Environment (CAVE) in 2010. With the new CAVE installed in 2017, CAES’s Applied Visualization Laboratory is even better equipped to provide researchers from universities, industry and government agencies with a user facility where they can visualize and address scientific and technical challenges.
Human System Simulation Laboratory (HSSL)
Human performance is the central theme in the research done in the HSSL. INL human factors researchers have extensive knowledge and experience of human performance in nuclear power operations and apply a wide range of human factors principles, methods and tools in solving practical and emerging problems in the energy sector. These include Task Analysis, Usability Engineering, Computational Human Performance Modeling, advanced Human-System Interface technologies, Human Reliability Analysis, and cognitive and physical ergonomics analyses.
A large part of the HSSL is devoted to the study of human performance in a near-realistic operational context. For this purpose, four light water reactor (LWR) plant models are used for assessment of human performance in a naturalistic setting. This includes studies in a range of focus areas:
- Usability of the HSI and benefits of advanced display technologies: This focuses on the effectiveness, efficiency, satisfaction, safety and reliability with which an operator can perform specific tasks in a specific operational context (normal or emergency). This includes the effect of new display technologies and different HSI configurations on human performance.
- Human performance, expressed as physical, mental and/or cognitive workload, under different operational conditions. This includes the typical operator functions:
Human error, human reliability and human error mechanisms
Situation awareness with a given HSI and control configuration under different operational conditions.
Human-system performance relationships: The relationship between the reliability of the operator, the time available to perform an action, and the influence of the performance characteristics of the plant or system on the task.
Crew communication effectiveness with given technologies under different operational conditions.
Human performance with different staffing configurations and with a given control room configuration.